Clinical risk factors for portal hypertension-related complications in systemic therapy for hepatocellular carcinoma

BACKGROUND

During systemic therapy, the management of portal hypertension (PH)-related complications is vital. This study aimed to clarify factors associated with the incidence and exacerbation of PH-related complications, including the usefulness of contrast-enhanced computed tomography (CECT) in the management of PH-related complications during systemic therapy.

METHODS

A total of 669 patients who received systemic therapy as first-line treatment (443 patients for sorafenib, 131 for lenvatinib, and 90 for atezolizumab/bevacizumab [ATZ/BEV]) were enrolled in this retrospective study. Additionally, the lower esophageal intramural vessel diameters (EIV) on CECT and endoscopic findings in 358 patients were compared.

RESULTS

The cutoff values of the EIV diameter on CECT were 3.1 mm for small, 5.1 mm for medium, and 7.6 mm for large varices, demonstrating high concordance with the endoscopic findings. esophageal varices (EV) bleeding predictors include EIV ≥ 3.1 mm and portal vein tumor thrombosis (PVTT). In patients without EV before systemic therapy, factors associated with EV exacerbation after 3 months were EIV ≥ 1.9 mm and ATZ/BEV use. Predictors of hepatic encephalopathy (HE) include the ammonia level or portosystemic shunt diameter ≥ 6.8 mm. The incidence of HE within 2 weeks was significantly higher (18%) in patients with an ammonia level ≥ 73 μmol/L and a portosystemic shunt ≥ 6.8 mm. The exacerbating factors for ascites after 3 months were PVTT and low albumin levels.

CONCLUSIONS

Careful management is warranted for patients with risk factors for exacerbation of PH-related complications; moreover, the effective use of CECT is clinically important.

Crossed raised arm position improves the flow of contrast medium in torso contrast-enhanced computed Tomography

INTRODUCTION

This retrospective cohort study examined the effects of the crossed raised arm (CRA) position in contrast-enhanced computed tomography (CECT) on contrast medium influx and image quality relative to the conventional position.

METHODS

Contrast medium influx into the collateral veins on CECT images was evaluated in 92 participants. The CT values of the pulmonary artery, descending aorta, and spleen were obtained in both positions and compared. Anatomical changes in the diameters and area of the subclavian vein and costoclavicular distance were also analyzed.

RESULTS

Contras 27 and 6 patients in the conventional and CRA positions, respectively. The influx risk ratio in the CRA position versus that in the conventional position was 0.22 (95% confidence interval, 0.10-0.51). Elevations in the median CT value of the pulmonary artery, descending aorta, and spleen in the CRA position were 7.0% (p < .001), 7.4% (p < .001), and 9.8% (p < .001), respectively. Enlargements in the major and minor diameters of the subclavian vein, subclavian vein area, and costoclavicular distance in the CRA position versus those in the conventional position were 19.3% (p < .001), 28.1% (p < .001), 53.6%, and 30.0% (p < .001), respectively.

CONCLUSION

The CRA position effectively prevented contrast medium influx into the collateral veins due to SVS and increased CT values in the target organs in CECT. The diameters and area of the subclavian vein and costoclavicular distance were enlarged at the thoracic outlet, which improved the flow of the contrast medium into the targeted organs.

IMPLICATIONS FOR PRACTICE

The CRA position can contribute to obtaining better CECT images during common clinical assessments at no additional cost.

An unexpected complication: Air embolism during contrast-enhanced computed tomography

Air embolism is often an iatrogenic complication that may occur in venous or arterial circulation depending on the port of entry. We present a case of a 40-year-old female who had a venous air embolism in the pulmonary artery as a consequence of the injection of a contrast agent. She experienced dyspnea and chest pain following a contrast-enhanced chest computed tomography imaging. She was successfully treated and discharged from our hospital. Early detection of this clinical condition is essential to prevent morbidity and mortality.

Urgent colonoscopy is not necessary in case of colonic diverticular bleeding without extravasation on contrast-enhanced computed tomography

BACKGROUND AND AIMS

Acute lower gastrointestinal bleeding (ALGIB) increase with age and the administration of antiplatelet drugs. Colonic diverticular bleeding (CDB) is the most common cause of ALGIB, and endoscopic hemostasis is an effective treatment for massive CDB. But in patients without extravasation on contrast-enhanced computed tomography (CECT), the efficacy of urgent colonoscopy (UCS) is controversial from the point of the clinical course, including rebleeding rate. We aimed to establish a potential strategy including UCS for CDB patients without extravasation on CECT.

PATIENTS AND METHODS

Patients from two centers treated for CDB without extravasation on CECT between July 2014 and July 2019 were retrospectively identified (n = 282). Seventy-four underwent UCS, and 208 received conservative management. We conducted two analyses. The first analysis investigates the risk factors of rebleeding rate within 5 days after administration (very early rebleeding), and no UCS (NUCS) was not the independent factor of the very early rebleeding. The second analysis is whether UCS positively influenced the clinical course after hospitalization.

RESULTS

The prevalence of very early rebleeding and early rebleeding (6-30 days from admission), patients requiring blood transfusion within 0-5 days and 6-30 days post-admission, and duration of hospitalization were examined as clinical course factors between UCS and NUCS group. There was no significant difference between the UCS and non-UCS groups in the clinical course factors. UCS for the CDB patients without extravasation was not improved rebleeding rate and clinical course.

CONCLUSIONS

UCS is not necessary in case ofCDB patient without extravasation on CECT.

Deep Learning Radiomics Nomogram Based on Multiphase Computed Tomography for Predicting Axillary Lymph Node Metastasis in Breast Cancer

PURPOSE

This study aims to develop and validate a deep learning radiomics nomogram (DLRN) for prediction of axillary lymph node metastasis (ALNM) in breast cancer patients.

MATERIALS AND METHODS

We retrospectively enrolled 196 patients with non-specific invasive breast cancer confirmed by pathology, radiomics and deep learning features were extracted from unenhanced and biphasic (arterial and venous phase) contrast-enhanced CT, and the non-linear support vector machine was used to construct the radiomics signature and the deep learning signature, respectively. Next, a DLRN was developed with independent predictors and evaluated the performance of models in terms of discrimination and clinical utility.

RESULTS

Multivariate logistic regression analysis showed that the radiomics signature, deep learning signature, and clinical n stage were independent predictors. The DLRN accurately predicted ALNM and yielded an area under the receiver operator characteristic curve of 0.893 (95% confidence interval, 0.814-0.972) in the validation set, with good calibration. Decision curve analysis confirmed that the DLRN had higher clinical utility than other predictors.

CONCLUSIONS

The DLRN had good predictive value for ALNM in breast cancer patients and provide valuable information for individual treatment.

Early encapsulation of peripancreatic fluid/necrosis collections on imaging (CECT) in acute pancreatitis: influential factors and clinical significance for prognosis

BACKGROUND

To identify the factors influencing the early encapsulation of peripancreatic fluid/necrosis collections via contrast-enhanced computed tomography (CECT) and to determine the clinical significance of early encapsulation for determining the prognosis of acute pancreatitis (AP) patients.

METHODS

AP patients who underwent CECT between 4 and 10 days after disease onset were enrolled in this study. Early encapsulation was defined as a continuous enhancing wall around peripancreatic fluid/necrosis collections on CECT. Univariate and multivariate logistic regression analyses were performed to assess the associations between the variables and early encapsulation. Clinical outcomes were compared between the non-encapsulation and early encapsulation groups with 1:1 propensity score matching.

RESULTS

A total of 289 AP patients were enrolled. The intra-observer and inter-observer agreement were considered good (kappa statistics of 0.729 and 0.614, respectively) for identifying early encapsulation on CECT. The ratio of encapsulation increased with time, with a ratio of 12.5% on day 5 to 48.7% on day 9. Multivariate logistic regression analysis revealed that the longer time from onset to CECT examination (OR 1.55, 95% CI 1.23-1.97), high alanine aminotransferase level (OR 0.98, 95% CI 0.97-0.99), and high APACHE II score (OR 0.89, 95% CI 0.81-0.98) were found to be independent factors associated with delayed encapsulation. The incidence of persistent organ failure was significantly lower in the early encapsulation group after matching (22.4% vs 6.1%, p = 0.043). However, there was no difference in the incidence of infected pancreatic necrosis, surgical intervention, or in-hospital mortality.

CONCLUSIONS

AP patients without early encapsulation of peripancreatic fluid/necrosis collections have a greater risk of persistent organ failure. In addition to longer time, the high APACHE II score and elevated alanine aminotransferase level are factors associated with delayed encapsulation.

An Evaluation Analysis for Computed Tomography Image Quality of Primary Liver Cancer Lesions Based on Deep Learning Image Reconstruction

BACKGROUND

Abdominal multi-slice helical computed tomography (CT) and contrast-enhanced scanning have been widely recognized clinically.

OBJECTIVE

The impact of the deep learning image reconstruction (DLIR) on the quality of dynamic contrast-enhanced CT imaging of primary liver cancer lesions was evaluated through comparison with the filtered back projection (FBP) and the new generation of adaptive statistical iterative reconstruction-V (ASIR-V).

METHODS

We evaluated the image noise of the lesion, fine structures inside the lesion, and diagnostic confidence in 48 liver cancer subjects. The CT values of the solid part of the lesion and the adjacent normal liver tissue and the systolic and diastolic blood pressure (SD) values of the right paravertebral muscle were measured. The muscle SD value was considered as the background noise of the image, and the signal noise ratio (SNR) and contrast signal-to-noise ratio (CNR) of the lesion and normal liver parenchyma were calculated.

RESULTS

High consistency in the evaluation of image noise (Kappa = 0.717). The Kappa values for margin/pseudocapsule, fine structure within the lesion, and diagnostic confidence were 0.463, 0.527, and 0.625, respectively. Besides, the differences in SD, SNR and CNR data of reconstructed lesion images among the six groups were statistically significant.

CONCLUSION

The contrast-enhanced CT image noise of DLIR-H in the portal venous phase is much lower than that of ASIR-V and FBP in primary liver cancer patients. In terms of the lesion structure display, the new reconstruction algorithm DLIR is superior.

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma

OBJECTIVES

In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT).

MATERIALS AND METHODS

CECT scans of 100 patients with OSCC (217 metastatic and 1973 non-metastatic cervical lymph nodes: development set, 76 patients; internally independent test set, 24 patients) who received treatment at the Peking University School and Hospital of Stomatology between 2012 and 2016 were retrospectively collected. Clinical diagnoses and pathological findings were used to establish the gold standard for metastatic cervical LNs. A reader study with two clinicians was also performed to evaluate the lymph node status in the test set. The performance of the proposed models and the clinicians was evaluated and compared by measuring using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE).

RESULTS

A fusion model combining deep learning with radiomics showed the best performance (ACC, 89.2%; SEN, 92.0%; SPE, 88.9%; and AUC, 0.950 [95% confidence interval: 0.908-0.993, P < 0.001]) in the test set. In comparison with the clinicians, the fusion model showed higher sensitivity (92.0 vs. 72.0% and 60.0%) but lower specificity (88.9 vs. 97.5% and 98.8%).

CONCLUSION

A fusion model combining radiomics and deep learning approaches outperformed other single-technique models and showed great potential to accurately predict cervical LNM in patients with OSCC.

CLINICAL RELEVANCE

The fusion model can complement the preoperative identification of LNM of OSCC performed by the clinicians.

Association of epicardial and intramyocardial fat with ventricular arrhythmias

BACKGROUND

Among patients with ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), myocardial fibrosis is associated with an increased risk for ventricular arrhythmia (VA). Growing evidence suggests that myocardial fat contributes to ventricular arrhythmogenesis. However, little is known about the volume and distribution of epicardial adipose tissue and intramyocardial fat and their relationship with VAs.

OBJECTIVE

The purpose of this study was to assess the association of contrast-enhanced computed tomography (CE-CT)-derived left ventricular (LV) tissue heterogeneity, epicardial adipose tissue volume, and intramyocardial fat volume with the risk of VA in ICM and NICM patients.

METHODS

Patients enrolled in the PROSE-ICD registry who underwent CE-CT were included. Intramyocardial fat volume (voxels between -180 and -5 Hounsfield units [HU]), epicardial adipose tissue volume (between -200 and -50 HU), and LV tissue heterogeneity were calculated. The primary endpoint was appropriate ICD shocks or sudden arrhythmic death.

RESULTS

Among 98 patients (47 ICM, 51 NICM), LV tissue heterogeneity was associated with VA (odds ratio [OR] 1.10; P = .01), particularly in the ICM cohort. In the NICM subgroup, epicardial adipose tissue and intramyocardial fat volume were associated with VA (OR 1.11, P = .01; and OR = 1.21, P = .01, respectively) but not in the ICM patients (OR 0.92, P =.22; and OR = 0.96, P =.19, respectively).

CONCLUSION

In ICM patients, increased fat distribution heterogeneity is associated with VA. In NICM patients, an increased volume of intramyocardial fat and epicardial adipose tissue is associated with a higher risk for VA. Our findings suggest that fat's contribution to VAs depends on the underlying substrate.

Development of real-time individualized risk prediction models for contrast associated acute kidney injury and 30-day dialysis after contrast enhanced computed tomography

PURPOSE

This study aimed to develop preprocedural real-time artificial intelligence (AI)-based systems for predicting individualized risks of contrast-associated acute kidney injury (CA-AKI) and dialysis requirement within 30 days following contrast-enhanced computed tomography (CECT).

METHOD

This single-center, retrospective study analyzed adult patients from emergency or in-patient departments who underwent CECT; 18,895 patients were included after excluding those who were already on dialysis, had stage V chronic kidney disease, or had missing data regarding serum creatinine levels within 7 days before and after CECT. Clinical parameters, laboratory data, medication exposure, and comorbid diseases were selected as predictive features. The patients were randomly divided into model training and testing groups at a 7:3 ratio. Logistic regression (LR) and random forest (RF) were employed to create prediction models, which were evaluated using receiver operating characteristic curves.

RESULTS

The incidence rates of CA-AKI and dialysis within 30 days post-CECT were 6.69% and 0.98%, respectively. For CA-AKI prediction, LR and RF exhibited similar performance, with areas under curve (AUCs) of 0.769 and 0.757, respectively. For 30-day dialysis prediction, LR (AUC, 0.863) and RF (AUC, 0.872) also exhibited similar performance. Relative to eGFR-alone, the LR and RF models produced significantly higher AUCs for CA-AKI prediction (LR vs. eGFR alone, 0.769 vs. 0.626, p < 0.001) and 30-day dialysis prediction (RF vs. eGFR alone, 0.872 vs. 0.738, p < 0.001).

CONCLUSIONS

The proposed AI prediction models significantly outperformed eGFR-alone for predicting the CA-AKI and 30-day dialysis risks of emergency department and hospitalized patients who underwent CECT.

Added value of CE-CT radiomics to predict high Ki-67 expression in hepatocellular carcinoma

BACKGROUND

This study aimed to develop a computed tomography (CT) model to predict Ki-67 expression in hepatocellular carcinoma (HCC) and to examine the added value of radiomics to clinico-radiological features.

METHODS

A total of 208 patients (training set, n = 120; internal test set, n = 51; external validation set, n = 37) with pathologically confirmed HCC who underwent contrast-enhanced CT (CE-CT) within 1 month before surgery were retrospectively included from January 2014 to September 2021. Radiomics features were extracted and selected from three phases of CE-CT images, least absolute shrinkage and selection operator regression (LASSO) was used to select features, and the rad-score was calculated. CE-CT imaging and clinical features were selected using univariate and multivariate analyses, respectively. Three prediction models, including clinic-radiologic (CR) model, rad-score (R) model, and clinic-radiologic-radiomic (CRR) model, were developed and validated using logistic regression analysis. The performance of different models for predicting Ki-67 expression was evaluated using the area under the receiver operating characteristic curve (AUROC) and decision curve analysis (DCA).

RESULTS

HCCs with high Ki-67 expression were more likely to have high serum α-fetoprotein levels (P = 0.041, odds ratio [OR] 2.54, 95% confidence interval [CI]: 1.04-6.21), non-rim arterial phase hyperenhancement (P = 0.001, OR 15.13, 95% CI 2.87-79.76), portal vein tumor thrombus (P = 0.035, OR 3.19, 95% CI: 1.08-9.37), and two-trait predictor of venous invasion (P = 0.026, OR 14.04, 95% CI: 1.39-144.32). The CR model achieved relatively good and stable performance compared with the R model (AUC, 0.805 [95% CI: 0.683-0.926] vs. 0.678 [95% CI: 0.536-0.839], P = 0.211; and 0.805 [95% CI: 0.657-0.953] vs. 0.667 [95% CI: 0.495-0.839], P = 0.135) in the internal and external validation sets. After combining the CR model with the R model, the AUC of the CRR model increased to 0.903 (95% CI: 0.849-0.956) in the training set, which was significantly higher than that of the CR model (P = 0.0148). However, no significant differences were found between the CRR and CR models in the internal and external validation sets (P = 0.264 and P = 0.084, respectively).

CONCLUSIONS

Preoperative models based on clinical and CE-CT imaging features can be used to predict HCC with high Ki-67 expression accurately. However, radiomics cannot provide added value.

Radiomics model based on contrast-enhanced computed tomography to predict early recurrence in patients with hepatocellular carcinoma after radical resection

BACKGROUND

Radical resection remains an effective strategy for patients with hepatocellular carcinoma (HCC). Unfortunately, the postoperative early recurrence (recurrence within 2 years) rate is still high.

AIM

To develop a radiomics model based on preoperative contrast-enhanced computed tomography (CECT) to evaluate early recurrence in HCC patients with a single tumour.

METHODS

We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection. First, the features from the portal venous and arterial phases of CECT were extracted based on the region of interest, and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model (LASSO Cox) to determine radiomics scores for each patient. Then, the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression. Finally, we evaluated the prediction performance of this model by multiple methods.

RESULTS

A total of 1915 radiomics features were extracted from CECT images, and 31 of them were used to determine the radiomics scores, which showed a significant difference between the early recurrence and nonearly recurrence groups. Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alpha-fetoprotein were independent indicators, and they were used to develop a combined model to predict early recurrence. The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74, respectively, while the C-indices were 0.712 and 0.674, respectively. The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities. Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.

CONCLUSION

The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.

Machine learning radiomics to predict the early recurrence of intrahepatic cholangiocarcinoma after curative resection: A multicentre cohort study

PURPOSE

Postoperative early recurrence (ER) leads to a poor prognosis for intrahepatic cholangiocarcinoma (ICC). We aimed to develop machine learning (ML) radiomics models to predict ER in ICC after curative resection.

METHODS

Patients with ICC undergoing curative surgery from three institutions were retrospectively recruited and assigned to training and external validation cohorts. Preoperative arterial and venous phase contrast-enhanced computed tomography (CECT) images were acquired and segmented. Radiomics features were extracted and ranked through their importance. Univariate and multivariate logistic regression analysis was used to identify clinical characteristics. Various ML algorithms were used to construct radiomics-based models, and the predictive performance was evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis.

RESULTS

127 patients were included for analysis: 90 patients in the training set and 37 patients in the validation set. Ninety-two patients (72.4%) experienced recurrence, including 71 patients exhibiting ER. Male sex, microvascular invasion, TNM stage, and serum CA19-9 were identified as independent risk factors for ER, with the corresponding clinical model having a poor predictive performance (AUC of 0.685). Fifty-seven differential radiomics features were identified, and the 10 most important features were utilized for modelling. Seven ML radiomics models were developed with a mean AUC of 0.87 ± 0.02, higher than the clinical model. Furthermore, the clinical-radiomics models showed similar predictive performance to the radiomics models (AUC of 0.87 ± 0.03).

CONCLUSION

ML radiomics models based on CECT are valuable in predicting ER in ICC.

What you need to know about: imaging in patients with renal failure

Contrast-enhanced medical imaging is commonly requested in clinical practice. Contrast media provide better differentiation of tissue enhancement, improves the soft tissue contrast resolution, and enhances the ability to study the physiology and function of the organs and/or systems. However, contrast media may cause complications, especially in patients with renal failure. This article discusses the use of contrast media in common imaging modalities and the relationship between contrast media and renal function. Administration of iodinated contrast media in computed tomography may cause contrast-associated acute kidney injury; the risk factors and preventive strategies for this are elaborated in this article. Administration of gadolinium-based contrast media in magnetic resonance imaging may lead to nephrogenic systemic fibrosis. Therefore, precautions should be taken when planning for medical imaging for patients with pre-existing acute kidney injury or end-stage chronic kidney disease, for whom contrast media administration in computed tomography or magnetic resonance imaging may be relatively contraindicated. Alternatively, ultrasound contrast agents can be safely used in patients with acute kidney injury or chronic kidney disease. Clinical teams should discuss these patients with radiologists, taking into account the risk-benefits of contrast media, to determine the optimal imaging protocol or modality to answer the clinical query.

Model integrating CT-based radiomics and genomics for survival prediction in esophageal cancer patients receiving definitive chemoradiotherapy

BACKGROUND

Definitive chemoradiotherapy (dCRT) is a standard treatment option for locally advanced stage inoperable esophageal squamous cell carcinoma (ESCC). Evaluating clinical outcome prior to dCRT remains challenging. This study aimed to investigate the predictive power of computed tomography (CT)-based radiomics combined with genomics for the treatment efficacy of dCRT in ESCC patients.

METHODS

This retrospective study included 118 ESCC patients who received dCRT. These patients were randomly divided into training (n = 82) and validation (n = 36) groups. Radiomic features were derived from the region of the primary tumor on CT images. Least absolute shrinkage and selection operator (LASSO) regression was conducted to select optimal radiomic features, and Rad-score was calculated to predict progression-free survival (PFS) in training group. Genomic DNA was extracted from formalin-fixed and paraffin-embedded pre-treatment biopsy tissue. Univariate and multivariate Cox analyses were undertaken to identify predictors of survival for model development. The area under the receiver operating characteristic curve (AUC) and C-index were used to evaluate the predictive performance and discriminatory ability of the prediction models, respectively.

RESULTS

The Rad-score was constructed from six radiomic features to predict PFS. Multivariate analysis demonstrated that the Rad-score and homologous recombination repair (HRR) pathway alterations were independent prognostic factors correlating with PFS. The C-index for the integrated model combining radiomics and genomics was better than that of the radiomics or genomics models in the training group (0.616 vs. 0.587 or 0.557) and the validation group (0.649 vs. 0.625 or 0.586).

CONCLUSION

The Rad-score and HRR pathway alterations could predict PFS after dCRT for patients with ESCC, with the combined radiomics and genomics model demonstrating the best predictive efficacy.

Hypoattenuated Area at Pancreatojejunostomy Site After Pancreatoduodenectomy Predicts Grade B/C Postoperative Pancreatic Fistula

BACKGROUND

After pancreatojejunostomy for pancreatic head resection, contrast-enhanced computed tomography sometimes reveals a hypoattenuated area at the pancreatojejunostomy site. The clinical impact of this hypoattenuated area, in terms of postoperative pancreatic fistula, is unknown.

METHODS

Among 309 patients undergoing pancreatic head resection with pancreatojejunostomy reconstruction at Osaka University Hospital from 2012 to 2020, 105 exhibited drain amylase levels over 3× the upper limit of normal. According to contrast-enhanced computed tomography on postoperative days 3-14, these patients were divided into two groups-evident hypoattenuated area group (≥ 5 mm; n = 46) and subtle hypoattenuated area group (< 5 mm; n = 59)-and evaluated for clinically relevant pancreatic fistula.

RESULTS

Clinically relevant pancreatic fistula was significantly more common with the evident hypoattenuated group (80.4%; 37/46) than the subtle hypoattenuated group (40.7%; 24/59) (P < 0.0001). Multivariate analysis identified four factors related to clinically relevant pancreatic fistula formation: male sex (P = 0.0230), main pancreatic duct diameter < 3 mm (P = 0.0007), operative time > 475 min (P = 0.0161), and evident hypoattenuated area group (P = 0.0050). Hypoattenuated area ≥ 5 mm was associated with clinically relevant pancreatic fistula (60.7% sensitivity; 79.6% specificity).

CONCLUSION

Evident hypoattenuated area on postoperative contrast-enhanced computed tomography was an independent risk factor for clinically relevant pancreatic fistula. Patients experiencing increased drain amylase levels may benefit from contrast-enhanced computed tomography assessment to predict clinically relevant pancreatic fistula formation.

Prospective Comparison of Oral Contrast-Enhanced Transabdominal Ultrasound Imaging With Contrast-Enhanced Computed Tomography in Pre-operative Tumor Staging of Gastric Cancer

The aim of this prospective study was to compare the diagnostic accuracy of oral contrast-enhanced transabdominal ultrasound imaging (OCTU) with that of contrast-enhanced computed tomography (CT) for the pre-operative tumor staging of gastric cancer, with post-operative pathology as the standard. We included 108 cases of gastric cancer with simultaneous OCTU and enhanced CT pre-operative tumor staging diagnoses. Results were compared with post-operative pathology based on the eighth edition of the American Joint Committee on Cancer tumor-node-metastasis staging guidelines for gastric cancer. The accuracy of each tumor stage was obtained by comparing OCTU and enhanced CT diagnoses with post-operative pathology. The McNemar test was used to compare the overall accuracy of the two methods. There was no statistical difference in accuracy between OCTU (72.2%) and enhanced CT (75.9%, p = 0.644) for overall pre-operative tumor staging diagnosis. For stages T1 to T4, the accuracy rates of OCTU were 84.2%, 81.8%, 69.4% and 65.5%, respectively, and those for enhanced CT were 52.6%, 72.7%, 87.8% and 72.4%, respectively. OCTU is comparable to enhanced CT in the preoperative overall T-stage diagnosis of gastric cancer.

Radiomics signatures based on contrast-enhanced CT for preoperative prediction of the Ki-67 proliferation state in gastrointestinal stromal tumors

PURPOSE

This study aimed to evaluate the Ki-67 proliferation state in patients with gastrointestinal stromal tumors (GISTs) using radiomics prediction signatures based on contrast-enhanced computed tomography (CE-CT).

MATERIALS AND METHODS

This single-center, retrospective study involved 103 patients (48 men and 55 women, mean age 61.1 ± 10.6 years) who had pathologically confirmed GISTs after curative resection, including 63 with low Ki-67 proliferation level (Ki-67 labeling index ≤ 6%) and 40 with high Ki-67 proliferation level (Ki-67 labeling index > 6%). Radiomics features of the delineated lesions were preoperatively extracted from three-phase CE-CT images, including the arterial, venous, and delayed phases. The most relevant features were selected to construct the radiomics signatures using a logistic regression algorithm. Significant demographic characteristics and semantic features on CT were selected to develop a nomogram along with the optimal radiomics feature. We calculated the sensitivity, specificity, accuracy, F1 score, and area under the receiver operating characteristic (ROC) curve to evaluate the predictive performance of radiomics signatures.

RESULTS

Ten quantitative radiomics features (two first-order and eight texture features) were selected to construct radiomics signatures. The radiomics signature based on the three-phase CE-CT images showed better predictive performance than that based on the single-phase CE-CT images, with an area under the curve (AUC) of 0.83 (95% CI 0.73-0.92) and F1 score of 82% in the training dataset and an AUC of 0.80 (95% CI 0.63-0.95) and F1 score of 75% in the testing dataset. The nomogram showed good calibration.

CONCLUSION

Radiomics signatures using CE-CT images are generalizable and could be used in clinical practice to determine the proliferation state of Ki-67 in GISTs.

Hematologic and inflammatory parameters for determining severity of odontogenic infections at admission: a retrospective study

BACKGROUND

Severe odontogenic infections in the head and neck region, especially necrotizing soft tissue infection (NSTI) and deep neck abscess, are potentially fatal due to their delayed diagnosis and treatment. Clinically, it is often difficult to distinguish NSTI and deep neck abscess in its early stage from cellulitis, and the decision to perform contrast-enhanced computed tomography imaging for detection is often a challenge. This retrospective case-control study aimed to examine the utility of routine blood tests as an adjunctive diagnostic tool for NSTI in the head and neck region and deep neck abscesses.

METHODS

Patients with severe odontogenic infections in the head and neck region that required hospitalization were classified into four groups. At admission, hematologic and inflammatory parameters were calculated according to the blood test results. In addition, a decision tree analysis was performed to detect NSTI and deep neck abscesses.

RESULTS

There were 271 patients, 45.4% in Group I (cellulitis), 22.5% in Group II (cellulitis with shallow abscess formation), 27.3% in Group III (deep neck abscess), and 4.8% in Group IV (NSTI). All hematologic and inflammatory parameters were higher in Groups III and IV. The Laboratory Risk Indicator for Necrotizing Fasciitis score, with a cut-off value of 6 and C-reactive protein (CRP) + the neutrophil-to-lymphocyte ratio (NLR), with a cut-off of 27, were remarkably useful for the exclusion diagnosis for Group IV. The decision tree analysis showed that the systemic immune-inflammation index (SII) of ≥ 282 or < 282 but with a CRP + NLR of ≥ 25 suggests Group III + IV and the classification accuracy was 89.3%.

CONCLUSIONS

Hematologic and inflammatory parameters calculated using routine blood tests can be helpful as an adjunctive diagnostic tool in the early diagnosis of potentially fatal odontogenic infections. An SII of ≥ 282 or < 282 but with a CRP + NLR of ≥ 25 can be useful in the decision-making for performing contrast-enhanced computed tomography imaging.

Pseudoileus caused by primary visceral myopathy in a Han Chinese patient with a rare MYH11 mutation: A case report

BACKGROUND

Chronic intestinal pseudo-obstruction (CIPO) is a syndrome of intestinal motor dysfunction caused by intestinal nerve, muscle, and/or Cajal stromal cell lesions. CIPO is a serious category of gastrointestinal dynamic dysfunction, which can eventually lead to the death of patients with intestinal failure. Due to considerable phenotypic heterogeneity, the estimated incidence of CIPO is 1/476190 and 1/416666 in men and women, respectively. According to the etiology, CIPO can be divided into idiopathic and secondary, of which the latter is the most common, often secondary to tumor, virus infection, connective tissue disease, neurological diseases, and endocrine diseases. Idiopathic CIPO in the intestinal tract is divided into visceral myopathy, neuropathy, and stromal cell lesions according to the location. Surgery is usually not recommended for CIPO, because it often does not benefit patients with CIPO, and postoperative intestinal obstruction is likely to occur, which may even worsen the condition.

CASE SUMMARY

Here, we describe the case of a 43-year-old male Han Chinese patient with a 15-year history of recurrent abdominal distention with no clear cause. The results of physical, biochemical, and other relevant examinations showed no clear abnormalities. Contrast-enhanced computed tomography (CT) indicated a large duodenum, clear expansion of the intestinal lumen, and CIPO. Whole exome sequencing (WES) of the patient and his mother confirmed the diagnosis of primary familial visceral myopathy type 2 chronic pseudoileus with a rare heterozygous gene mutation in MYH11. This is the second reported case of CIPO with a heterozygous MYH11 [NM_001040113.1: c.5819delC (p.Pro1940Hisfs*91)] mutation.

CONCLUSION

This case report indicates that physicians can perform routine clinical examinations, CT, and WES to achieve a diagnosis and treatment of CIPO in early disease stages.

Diagnostic performance of abbreviated gadoxetic acid-enhanced magnetic resonance protocols with contrast-enhanced computed tomography for detection of colorectal liver metastases

BACKGROUND

Although contrast-enhanced magnetic resonance imaging (MRI) using gadoxetic acid has been shown to have higher accuracy, sensitivity, and specificity for the detection and characterization of hepatic metastases compared with other modalities, the long examination time would limit the broad indication. Several abbreviated enhanced MRI (Ab-MRI) protocols without dynamic phases have been proposed to achieve equivalent diagnostic performance for the detection of colorectal liver metastases. However, an optimal protocol has not been established, and no studies have assessed the diagnostic performance of Ab-MRI combined with contrast-enhanced computed tomography (CE-CT), which is the preoperative imaging of colorectal cancer staging in clinical settings, to determine the best therapeutic strategy.

AIM

To compare the diagnostic performance of two kinds of Ab-MRI protocol with the standard MRI protocol and a combination of the Ab-MRI protocol and CE-CT for the detection of colorectal liver metastases.

METHODS

Study participants comprised 87 patients (51 males, 36 females; mean age, 67.2 ± 10.8 years) who had undergone gadoxetic acid-enhanced MRI and CE-CT during the initial work-up for colorectal cancer from 2010 to 2021. Each exam was independently reviewed by two readers in three reading sessions: (1) Only single-shot fast spin echo (FSE) T2-weighted or fat-suppressed-FSE-T2-weighted, diffusion-weighted, and hepatobiliary-phase images (Ab-MRI protocol 1 or 2); (2) all acquired MRI sequences (standard protocol); and (3) a combination of an Ab-MRI protocol (1 or 2) and CE-CT. Diagnostic performance was then statistically analyzed.

RESULTS

A total of 380 Lesions were analyzed, including 195 metastases (51.4%). Results from the two Ab-MRI protocols were similar. The sensitivity, specificity, and positive and negative predictive values from Ab-MRI were non-inferior to those from standard MRI (P > 0.05), while those from the combination of Ab-MRI protocol and CE-CT tended to be higher than those from Ab-MRI alone, although the difference was not significant (P > 0.05), and were quite similar to those from standard MRI (P > 0.05).

CONCLUSION

The diagnostic performances of two Ab-MRI protocols were non-inferior to that of the standard protocol. Combining Ab-MRI with CE-CT provided better diagnostic performance than Ab-MRI alone.

Cavernous hemangioma of the ileum in a young man: A case report and review of literature

BACKGROUND

Small intestinal cavernous hemangioma is a rare disease, especially in the ileum. It is difficult to accurately diagnose due to its hidden location and nonspecific clinical symptoms. Here, we reported a case of ileal cavernous hemangioma with chronic hemorrhage in a 20-year-old man and review the literature to gain a better understanding of this disease.

CASE SUMMARY

The patient complained of intermittent melena and hematochezia for > 3 mo. The lowest hemoglobin level revealed by laboratory testing was 3.4 g/dL (normal range: 12-16 g/dL). However, the gastroscopy, colonoscopy and peroral double-balloon enteroscopy (DBE) showed no signs of bleeding. The transanal DBE detected a lesion at about 340 cm proximal to the ileocecal valve. Thus, we performed an exploratory laparoscopy and the lesion was resected. After the operation, the patient had no melena. Finally, the pathological examination identified the neoplasm as an ileal cavernous hemangioma, thereby resulting in gastrointestinal hemorrhage.

CONCLUSION

This report might improve the diagnosis and treatment of ileal cavernous hemangioma.

Relapsing low-flow alarms due to suboptimal alignment of the left ventricular assist device inflow cannula

OBJECTIVES

This retrospective study investigated the correlation between the angular position of the left ventricular assist device (LVAD) inflow cannula and relapsing low-flow alarms.

METHODS

Medical charts were reviewed of all patients with HeartMate 3 LVAD support for relapsing low-flow alarms. A standardized protocol was created to measure the angular position with a contrast-enhanced computed tomography scan. Statistics were done using a gamma frailty model with a constant rate function.

RESULTS

For this analysis, 48 LVAD-supported patients were included. The majority of the patients were male (79%) with a median age of 57 years and a median follow-up of 30 months (interquartile range: 19-41). Low-flow alarm(s) were experienced in 30 (63%) patients. Angulation towards the septal-lateral plane showed a significant increase in low-flow alarms over time with a constant rate function of 0.031 increase in low-flow alarms per month of follow-up per increasing degree of angulation (P = 0.048). When dividing this group using an optimal cut-off point, a significant increase in low-flow alarms was observed when the septal-lateral angulation was 28° or more (P = 0.001). Anterior-posterior and maximal inflow cannula angulation did not show a significant difference.

CONCLUSIONS

This study showed an increasing number of low-flow alarms when the degrees of LVAD inflow cannula expand towards the septal-lateral plane. This emphasizes the importance of the LVAD inflow cannula angular position to prevent relapsing low-flow alarms with the risk of diminished quality of life and morbidity.

Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with a rising incidence worldwide. The prognosis of HCC patients after radical resection remains poor. Radiomics is a novel machine learning method that extracts quantitative features from medical images and provides predictive information of cancer, which can assist with cancer diagnosis, therapeutic decision-making and prognosis improvement.

AIM

To develop and validate a contrast-enhanced computed tomography-based radiomics model for predicting the overall survival (OS) of HCC patients after radical hepatectomy.

METHODS

A total of 150 HCC patients were randomly divided into a training cohort (n = 107) and a validation cohort (n = 43). Radiomics features were extracted from the entire tumour lesion. The least absolute shrinkage and selection operator algorithm was applied for the selection of radiomics features and the construction of the radiomics signature. Univariate and multivariate Cox regression analyses were used to identify the independent prognostic factors and develop the predictive nomogram, incorporating clinicopathological characteristics and the radiomics signature. The accuracy of the nomogram was assessed with the concordance index, receiver operating characteristic (ROC) curve and calibration curve. The clinical utility was evaluated by decision curve analysis (DCA). Kaplan–Meier methodology was used to compare the survival between the low- and high-risk subgroups.

RESULTS

In total, seven radiomics features were selected to construct the radiomics signature. According to the results of univariate and multivariate Cox regression analyses, alpha-fetoprotein (AFP), neutrophil-to-lymphocyte ratio (NLR) and radiomics signature were included to build the nomogram. The C-indices of the nomogram in the training and validation cohorts were 0.736 and 0.774, respectively. ROC curve analysis for predicting 1-, 3-, and 5-year OS confirmed satisfactory accuracy [training cohort, area under the curve (AUC) = 0.850, 0.791 and 0.823, respectively; validation cohort, AUC = 0.905, 0.884 and 0.911, respectively]. The calibration curve analysis indicated a good agreement between the nomogram-prediction and actual survival. DCA curves suggested that the nomogram had more benefit than traditional staging system models. Kaplan–Meier survival analysis indicated that patients in the low-risk group had longer OS and disease-free survival (all P < 0.0001).

CONCLUSION

The nomogram containing the radiomics signature, NLR and AFP is a reliable tool for predicting the OS of HCC patients.

Differential diagnosis and prognosis of small renal masses: association with collateral vessels detected using contrast-enhanced computed tomography

Background

Active surveillance (AS) is one of the treatment methods for patients with small renal masses (SRMs; < 4 cm), including renal cell carcinomas (RCCs). However, some small RCCs may exhibit aggressive neoplastic behaviors and metastasize. Little is known about imaging biomarkers capable of identifying potentially aggressive small RCCs. Contrast-enhanced computed tomography (CECT) often detects collateral vessels arising from neoplastic angiogenesis in RCCs. Therefore, this study aimed to evaluate the association between SRM differential diagnoses and prognoses, and the detection of collateral vessels using CECT.

Methods

A total of 130 consecutive patients with pathologically confirmed non-metastatic SRMs (fat-poor angiomyolipomas [fpAMLs; n = 7] and RCCs [n = 123]) were retrospectively enrolled. Between 2011 and 2019, SRM diagnoses in these patients were confirmed after biopsy or surgical resection. All RCCs were surgically resected. Regardless of diameter, a collateral vessel (CV) was defined as any blood vessel connecting the tumor from around the kidney using CECT. First, we analyzed the role of CV-detection in differentiating between fpAML and RCC. Then, we evaluated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of RCC diagnosis based on CV-detection using CECT. We also assessed the prognostic value of CV-detection using the Fisher exact test, and Kaplan-Meier method and the log-rank test.

Results

The sensitivity, specificity, PPV, NPV, and accuracy of CV-detection for the diagnosis of small RCCs was 48.5, 45.5, 100, 100, and 9.5% respectively. Five of 123 (4.1%) patients with RCC experienced recurrence. CV-detection using CECT was the only significant factor associated with recurrence (p = 0.0177). Recurrence-free survival (RFS) was significantly lower in patients with CV compared with in those without CV (5-year RFS 92.4% versus 100%, respectively; p = 0.005). In addition, critical review of the CT images revealed the CVs to be continuous with the venous vessels around the kidney.

Conclusions

The detection of CVs using CECT is useful for differentiating between small fpAMLs and RCCs. CV-detection may also be applied as a predictive parameter for small RCCs prone to recurrence after surgical resection. Moreover, AS could be suitable for small RCCs without CVs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09971-w.

Preoperative CECT-based Radiomic Signature for Predicting the Response of Transarterial Chemoembolization (TACE) Therapy in Hepatocellular Carcinoma

PURPOSE

To evaluate the efficiency of radiomics signatures in predicting the response of transarterial chemoembolization (TACE) therapy based on preoperative contrast-enhanced computed tomography (CECT).

MATERIALS

This study consisted of 111 patients with intermediate-stage hepatocellular carcinoma who underwent CECT at both the arterial phase (AP) and venous phase (VP) before and after TACE. According to mRECIST 1.1, patients were divided into an objective-response group (n = 38) and a non-response group (n = 73). Among them, 79 patients were assigned as the training dataset, and the remaining 32 cases were assigned as the test dataset.

METHODS

Radiomics features were extracted from CECT images. Two feature ranking methods and three classifiers were used to find the best single-phase radiomics signatures for both AP and VP on the training set. Meanwhile, multi-phase radiomics signatures were built upon integration of images from two CECT phases by decision-level fusion and feature-level fusion. Finally, multivariable logistic regression was used to develop a nomogram by combining radiomics signatures and clinic-radiologic characteristics. The prediction performance was evaluated by AUC on the test dataset.

RESULTS

The multi-phase radiomics signature (AUC = 0.883) performed better in predicting TACE therapy response compared to the best single-phase radiomics signature (AUC = 0.861). The nomogram (AUC = 0.913) showed better performance than any radiomics signatures.

CONCLUSION

The radiomics signatures and nomogram were developed and validated for predicting responses to TACE therapy, and the radiomics model may play a positive role in identifying patients who may benefit from TACE therapy in clinical practice.

The diagnostic performance of contrast-enhanced CT versus extracellular contrast agent-enhanced MRI in detecting hepatocellular carcinoma: direct comparison and a meta-analysis

To compare the diagnostic value of contrast-enhanced computed tomography (CT) with extracellular contrast agent-enhanced magnetic resonance imaging (ECA-MRI) for the detection of hepatocellular carcinoma (HCC). Pubmed, Embase, Web of Science and Cochrane Library were searched (1/5/2021) for studies comparing contrast-enhanced CT with ECA-MRI in patients suspected of HCC. Studies without head-to-head comparison were excluded. The pooled sensitivity, specificity and summary area under the curve (sAUC) of contrast-enhanced CT and ECA-MRI in detecting HCC was calculated based on bivariate random effects model. Heterogeneity test included threshold effect analysis and meta-regression. Subgroup analyses were conducted according to lesion size (< 20 mm or ≥ 20 mm). Overall, 10 articles containing 1333 patients were deemed suitable for inclusion in this meta-analysis. ECA-MRI displayed increased sensitivity to contrast-enhanced CT in detecting HCC (0.77 vs. 0.63, P < 0.01). The difference in specificity between ECA-MRI and contrast-enhanced CT was not statistically significant (0.93 vs. 0.94, P = 0.25). ECA-MRI yielded higher diagnostic accuracy (sAUCs = 0.88 vs. 0.80, P < 0.01). In the subgroup analysis with a lesion size < 20 mm, ECA-MRI allowed significant gains of accuracy compared to contrast-enhanced CT (0.79 vs. 0.72, P = 0.02). ECA-MRI also outperformed contrast-enhanced CT in patients with lesion size ≥ 20 mm (sAUCs = 0.96 vs. 0.93, P = 0.04). ECA-MRI provided higher sensitivity and accuracy than contrast-enhanced CT in detecting HCC, especially lesions size < 20 mm.

Radiomics Nomogram Based on Contrast-enhanced CT to Predict the Malignant Potential of Gastrointestinal Stromal Tumor: A Two-center Study

RATIONALE AND OBJECTIVES

Contrast-enhanced computed tomography (CE-CT) was used to establish radiomics nomogram to evaluate the malignant potential of gastrointestinal stromal tumors (GISTs).

MATERIALS AND METHODS

A total of 500 GIST patients were enrolled in this study and divided into training cohort (n = 346, our center) and validation cohort (n = 154, another center). Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithms were used to select the feature subset with the best discriminant features from the three phases image, and five classifiers were used to establish four radiomics signatures. Preoperative radiomics nomogram was constructed by adding the clinical features determined by multivariate logistic regression analysis. The performance of radiomics signatures and nomogram were evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC). The calibration of nomogram was appraised by calibration curve.

RESULTS

A total of 13 radiomic features were extracted from tri-phase combined CE-CT images. Tri-phase combined CE-CT features + Support Vector Machine (SVM) was the best combination at predicting the malignant potential of GIST, with an AUC of 0.895 (95% CI 0.858-0.931) in the training cohort and 0.847 (95% CI 0.778-0.917) in the validation cohort. The nomogram also had good calibration. In the training cohort and the validation cohort, preoperative radiomics nomogram reached AUCs of 0.927 and 0.905, respectively, which were higher than clinical.

CONCLUSION

The radiomics nomogram had a good predictive effect and generalization on the malignant potential of GIST, which could effectively help guide preoperative clinical decision.

Can lymphovascular invasion be predicted by contrast-enhanced CT imaging features in patients with esophageal squamous cell carcinoma? A preliminary retrospective study

Background

To investigate the value of contrast-enhanced CT (CECT)-derived imaging features in predicting lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC) patients.

Methods

One hundred and ninety-seven patients with postoperative pathologically confirmed esophageal squamous cell carcinoma treated in our hospital between January 2017 and January 2019 were enrolled in our study, including fifty-nine patients with LVI and one hundred and thirty-eight patients without LVI. The CECT-derived imaging features of all patients were analyzed. The CECT-derived imaging features were divided into quantitative features and qualitative features. The quantitative features consisted of the CT attenuation value of the tumor (CTV_Tumor), the CT attenuation value of the normal esophageal wall (CTV_Normal), the CT attenuation value ratio of the tumor-to-normal esophageal wall (TNR), the CT attenuation value difference between the tumor and normal esophageal wall (ΔTN), the maximum thickness of the tumor measured by CECT (Thickness), the maximum length of the tumor measured by CECT (Length), and the gross tumor volume measured by CECT (GTV). The qualitative features consisted of an enhancement pattern, tumor margin, enlarged blood supply or drainage vessels to the tumor (EVFDT), and tumor necrosis. For the clinicopathological characteristics and CECT-derived imaging feature analysis, the chi-squared test was used for categorical variables, the Mann–Whitney U test was used for continuous variables with a nonnormal distribution, and the independent sample t-test was used for the continuous variables with a normal distribution. The trend test was used for ordinal variables. The association between LVI status and CECT-derived imaging features was analyzed by univariable logistic analysis, followed by multivariable logistic regression and receiver operating characteristic (ROC) curve analysis.

Results

The CTV_Tumor, TNR, ΔTN, Thickness, Length, and GTV in the group with LVI were higher than those in the group without LVI (P < 0.05). A higher proportion of patients with heterogeneous enhancement pattern, irregular tumor margin, EVFDT, and tumor necrosis were present in the group with LVI (P < 0.05). As revealed by the univariable logistic analysis, the CECT-derived imaging features, including CTV_Tumor, TNR, ΔTN and enhancement pattern, Thickness, Length, GTV, tumor margin, EVFDT, and tumor necrosis were associated with LVI status (P < 0.05). Only the TNR (OR 8.655; 95% CI 2.125–37.776), Thickness (OR 6.531; 95% CI 2.410–20.608), and tumor margin (OR 4.384; 95% CI 2.004–9.717) were independent risk factors for LVI in the multivariable logistic regression analysis. The ROC curve analysis incorporating the above three CECT-derived imaging features showed that the area under the curve obtained by the multivariable logistic regression model was 0.820 (95% CI 0.754–0.885).

Conclusion

The CECT-derived imaging features, including TNR, Thickness, tumor margin, and their combination, can be used as predictors of LVI status for patients with ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00804-7.

Primary pulmonary meningioma: A case report and review of the literature

BACKGROUND

Primary pulmonary meningioma (PPM) is a rare disease that is usually benign. The most common presentation of PPM is isolated pulmonary nodules or masses, so the disease can mimic any other lung tumor on imaging, especially lung cancer or metastasis.

CASE SUMMARY

A 47-year-old asymptomatic woman presented with a well-defined, lobulated pulmonary mass with calcification in the left lower lobe. The mass measured 69 mm × 57 mm × 61 mm and was found during a chest computed tomography (CT) performed for physical examination. Contrast-enhanced CT and positron emission tomography (PET)/CT revealed mild enhancement of the mass, with accumulation of 18-fluoro-2-deoxy-D-glucose (¹⁸F-FDG). Transbronchial biopsy suggested a provisional diagnosis of low-grade neuroendocrine tumor. Subsequent enhanced head magnetic resonance imaging revealed no positive lesions. An open cuff resection of the left lower lobe and wedge resection of the lingual segment were performed. Histopathological and immunohistochemical examination revealed that the mass was a PPM.

CONCLUSION

PPM should be considered in the differential diagnosis of isolated pulmonary masses found incidentally on CT and should be diagnosed based on a combination of radiological and histological features. Surgical resection is currently the main treatment strategy. No recurrence of benign PPMs has been reported after complete resection.

The utility of using TACE-assisted software with CBCT in colonic diverticular bleeding without extravascular leakage

The utility of three-dimensional (3D) imaging with cone-beam computed tomography (CBCT) during interventional radiology (IVR) in colonic diverticular bleeding was compared to that of contrast-enhanced computed tomography (CECT). Additionally, to identify the responsible vessels in the absence of extravascular leakage using digital subtraction angiography, we examined the detection rate using software conventionally applied to transcatheter arterial chemoembolization (TACE). The 3D images obtained by CECT before IVR did not clearly show the destroyed vessels, whereas the 3D images obtained by CBCT during IVR clearly depicted the peripheral vessels. The TACE-assisted software identified the responsible vessels with a high probability, even in cases without extravascular leakage. CBCT could delineate vascular positions more accurately than CECT. Moreover, 80% of the responsible vessels could be delineated using the software; however, caution should be exercised as results may differ depending on the positioning of the region of interest.

Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility study

BACKGROUND

Adjuvant radiation therapy improves the overall survival and loco-regional control in patients with breast cancer. However, radiation-induced heart disease, which occurs after treatment from incidental radiation exposure to the cardiac organ, is an emerging challenge. This study aimed to generate synthetic contrast-enhanced computed tomography (SCECT) from non-contrast CT (NCT) using deep learning (DL) and investigate its role in contouring cardiac substructures. We also aimed to determine its applicability for a retrospective study on the substructure volume-dose relationship for predicting radiation-induced heart disease.

METHODS

We prepared NCT-CECT cardiac scan pairs of 59 patients. Of these, 35, 4, and 20 pairs were used for training, validation, and testing, respectively. We adopted conditional generative adversarial network as a framework to generate SCECT. SCECT was validated in the following three stages: (1) The similarity between SCECT and CECT was evaluated; (2) Manual contouring was performed on SCECT and CECT with sufficient intervals and based on this, the geometric similarity of cardiac substructures was measured between them; (3) The treatment plan was quantitatively analyzed based on the contours of SCECT and CECT.

RESULTS

While the mean values (± standard deviation) of the mean absolute error, peak signal-to-noise ratio, and structural similarity index measure between SCECT and CECT were 20.66 ± 5.29, 21.57 ± 1.85, and 0.77 ± 0.06, those were 23.95 ± 6.98, 20.67 ± 2.34, and 0.76 ± 0.07 between NCT and CECT, respectively. The Dice similarity coefficients and mean surface distance between the contours of SCECT and CECT were 0.81 ± 0.06 and 2.44 ± 0.72, respectively. The dosimetry analysis displayed error rates of 0.13 ± 0.27 Gy and 0.71 ± 1.34% for the mean heart dose and V5Gy, respectively.

CONCLUSION

Our findings displayed the feasibility of SCECT generation from NCT and its potential for cardiac substructure delineation in patients who underwent breast radiation therapy.

Risk Stratification and Distribution of Hepatocellular Carcinomas in CEUS and CT/MRI LI-RADS: A Meta-Analysis

Background

CEUS LI-RADS and CT/MRI LI-RADS have been used in clinical practice for several years. However, there is a lack of evidence-based study to compare the proportion of hepatocellular carcinomas (HCCs) in each category and the distribution of HCCs of these two categorization systems.

Purpose

The purpose of this study was to compare the proportion of HCCs between corresponding CEUS LI-RADS and CT/MRI LI-RADS categories and the distribution of HCCs and non-HCC malignancies in each category.

Methods

We searched PubMed, Embase, and Cochrane Central databases from January 2014 to December 2021. The proportion of HCCs and non-HCC malignancies and the corresponding sensitivity, specificity, accuracy, diagnostic odds ratio (DOR), and area under the curve (AUC) of the LR-5 and LR-M categories were determined using a random-effect model.

Results

A total of 43 studies were included. The proportion of HCCs in CEUS LR-5 was 96%, and that in CECT/MRI LR-5 was 95% (p > 0.05). The proportion of non-HCC malignancy in CEUS LR-M was lower than that of CT/MRI LR-M (35% vs. 58%, p = 0.01). The sensitivity, specificity, and accuracy of CEUS LR-5 for HCCs were 73%, 92%, and 78%, respectively, and of CT/MRI LR-5 for HCCs, 69%, 92%, and 76%, respectively.

Conclusion

With the upshift of the LI-RADS category, the proportion of HCCs increased. CEUS LR-3 has a lower risk of HCCs than CT/MRI LR-3. CEUS LR-5 and CT/MRI LR-5 have a similar diagnostic performance for HCCs. CEUS LR-M has a higher proportion of HCCs and a lower proportion of non-HCC malignancies compared with CT/MRI LR-M.

Morphologic Severity of Acute Pancreatitis on Imaging Is Independently Associated with Opioid Dose Requirements in Hospitalized Patients

BACKGROUND

Prior studies have evaluated clinical characteristics associated with opioid dose requirements in hospitalized patients with acute pancreatitis (AP) but did not incorporate morphologic findings on CT imaging.

AIMS

We sought to determine whether morphologic severity on imaging is independently associated with opioid dose requirements in AP.

METHODS

Adult inpatients with a diagnosis of AP from 2006 to 2017 were reviewed. The highest modified CT severity index (MCTSI) score and the daily oral morphine equivalent (OME) for each patient over the first 7 days of hospitalization were used to grade the morphologic severity of AP and calculate mean OME per day(s) of treatment (MOME), respectively. Multiple regression analysis was used to evaluate the association of MOME with MCSTI.

RESULTS

There were 249 patients with AP, of whom 196 underwent contrast-enhanced CT. The mean age was 46 ± 13.6 years, 57.9% were male, and 60% were black. The mean MOME for the patient cohort was 60 ± 52.8 mg/day. MCTSI (β = 3.5 [95% CI 0.3, 6.7], p = 0.03), early hemoconcentration (β = 21 [95% CI 4.6, 39], p = 0.01) and first episode of AP (β =  - 17 [95% CI - 32, - 2.7], p = 0.027) were independently associated with MOME. Among the 19 patients undergoing ≥ 2 CT scans, no significant differences in MOME were seen between those whose MCTSI score increased (n = 12) versus decreased/remained the same (n = 7).

CONCLUSION

The morphologic severity of AP positively correlated with opioid dose requirements. No difference in opioid dose requirements were seen between those who did versus those who did not experience changes in their morphologic severity.

Efficacy of non-obstructive aortic angioscopy for detecting a thoracic aortic graft rupture: a case report

Background

Non-anastomotic thoracic aortic graft rupture is extremely rare and difficult to diagnose. Non-obstructive general angioscopy can help monitor the aortic intima and detect the locations of abnormal findings, while aortic angioscopy can detect vulnerable plaques in the aorta, which are difficult to visualize using conventional diagnostic methods. Herein, we report the case of a patient with non-anastomotic thoracic aortic graft rupture diagnosed using non-obstructive aortic angioscopy.

Case presentation

An 85-year-old man who had undergone total arch replacement 5 years prior complained of chest pain. Emergent contrast-enhanced computed tomography (CT) revealed an intra-mediastinal hematoma around the vascular graft of the ascending aorta and angiography revealed pooling of contrast medium on the dorsal side of the vascular graft. We suspected extravasation of the thoracic vascular graft. Aortic angioscopic examination revealed a red vascular graft defect that matched extravasation at the contralateral level of the prosthetic left common carotid artery branch. Subsequently, non-anastomotic thoracic aortic graft rupture was diagnosed. The patient underwent a two-debranching thoracic endovascular aortic repair (Zone 0) with a right subclavian artery-left common carotid artery-left subclavian artery bypass. Postoperative angiography revealed disappearance of the extravasation from the graft rupture site, patent grafted vessels with flow, and no endoleak. Follow-up CT at 6 months postoperatively showed no extravasation.

Conclusions

To our knowledge, this is the first report of non-anastomotic thoracic aortic graft rupture detected using non-obstructive aortic angioscopy. Aortic angioscopy can help establish a definitive diagnosis in patients with aortic graft rupture.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40792-022-01394-w.

CT findings in renovascular injuries following abdominal trauma: a pictorial review

Renal vascular injuries are more devastating than parenchymal injuries alone, thus account for higher injury grade and require prompt recognition. Revised AAST organ injury scale (OIS) for renal trauma has incorporated CT-diagnosed vascular injuries into renal injury grading which includes pseudoaneurysm and arteriovenous fistula, along with addition of some new descriptors of renovascular injury. Dual-phase contrast-enhanced CT (with both arterial and venous phase) can easily pick up renovascular injuries and is the modality of choice for imaging renovascular trauma. Radiologist should be well versed with the imaging findings of renovascular injuries so that accurate injury grading can be done and further management can be planned at the earliest.

Development and Validation of a CT-Based Signature for the Prediction of Distant Metastasis Before Treatment of Non-Small Cell Lung Cancer

RATIONALE AND OBJECTIVES

To develop and validate a radiomics model, a clinical-semantic model and a combined model by using standard methods for the pretreatment prediction of distant metastasis (DM) in patients with non-small-cell lung cancer (NSCLC) and to explore whether the combined model provides added value compared to the individual models.

MATERIALS AND METHODS

This retrospective study involved 356 patients with NSCLC. According to the image biomarker standardization initiative reference manual, we standardized the image processing and feature extraction using in-house software. Finally, 6692 radiomics features were extracted from each lesion based on contrast-enhanced chest CT images. The least absolute shrinkage selection operator and the recursive feature elimination algorithm were used to select features. The logistic regression classifier was used to build the model. Three models (radiomics model, clinical-semantic model and combined model) were constructed to predict DM in NSCLC. Area under the receiver operating characteristic curves were used to validate the ability of the three models to predict DM. A visual nomogram based on the combined model was developed for DM risk assessment in each patient.

RESULTS

The receiver operating characteristic curve showed predictive performance for DM of the radiomics model (area under the curve [AUC] values for training and validation were 0.76 [95% CI, 0.704 - 0.820] and 0.76 [95% CI, 0.653 - 0.858], respectively). The combined model had AUCs of 0.78 (95% CI, 0.723 - 0.835) and 0.77 (95% CI, 0.673 - 0.870) in the training and validation cohorts, respectively. Both the radiomics model and combined model performed better than the clinical-semantic model (0.70 [95% CI, 0.634 - 0.760] and 0.67 [95% CI, 0.554 - 0.787] in the training and validation cohorts, respectively).

CONCLUSION

The radiomics model and combined model may be useful for the prediction of DM in patients with NSCLC.

Characteristics of false-positive lesions in evaluating colorectal liver metastases on gadoxetic acid-enhanced magnetic resonance imaging

PURPOSE

Gadoxetic acid-enhanced MRI (Gd-EOB-MRI) shows higher sensitivity for colorectal liver metastases (CRLM) than contrast-enhanced computed tomography (CECT). However, the details of false-positive lesions for each imaging modality are unknown.

METHODS

Cases undergoing hepatectomy for CRLM following a preoperative evaluation with both CECT and Gd-EOB-MRI between July 2008 and December 2016 were reviewed. The false-positive and false-negative rates were assessed for each modality, and the characteristics of false-positive lesions were evaluated.

RESULTS

We evaluated 275 partial hepatectomies in 242 patients without preoperative chemotherapy. Among the 275 hepatectomies, 546 lesions were recognized by CECT and/or Gd-EOB-MRI. The false-positive rates for CECT and Gd-EOB-MRI were 4% (18/422) and 7% (37/536), respectively. The size of false-positive lesions was significantly smaller than that of correctly diagnosed lesions (median: 28 mm [3-120 mm] vs 7.6 mm [320 mm], P  < 0.001). Compared with the 233 correctly diagnosed lesions ≤ 20 mm in diameter, false-positive lesions were more frequently located near the liver surface or vasculobiliary structures than true lesions (33/37 [89%] vs 149/233 [64%], respectively; P  = 0.0021).

CONCLUSION

Gd-EOB-MRI had a 7% false-positive rate. A small size and tumor location near the surface or near vasculobiliary structures were associated with false positivity.

Contrast-enhanced computed tomography radiomics and multilayer perceptron network classifier: an approach for predicting CD20+ B cells in patients with pancreatic ductal adenocarcinoma

PURPOSE

To develop and validate a machine-learning classifier based on contrast-enhanced computed tomography (CT) for the preoperative prediction of CD20⁺ B lymphocyte expression in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Overall, 189 patients with PDAC (n = 132 and n = 57 in the training and validation sets, respectively) underwent immunohistochemistry and radiomics feature extraction. The X-tile software was used to stratify them into groups with 'high' and 'low' CD20⁺ B lymphocyte expression levels. For each patient, 1409 radiomic features were extracted from volumes of interest and reduced using variance analysis and Spearman correlation analysis. A multilayer perceptron (MLP) network classifier was developed using the training and validation set. Model performance was determined by its discriminative ability, calibration, and clinical utility.

RESULTS

A log-rank test showed that the patients with high CD20⁺ B expression had significantly longer survival than those with low CD20⁺ B expression. The prediction model showed good discrimination in both the training and validation sets. For the training set, the area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.82 (95% CI 0.74-0.89), 92.42%, 57.58%, 0.75, 0.69, and 0.88, respectively; whereas these values for the validation set were 0.84 (95% CI 0.72-0.93), 86.21%, 78.57%, 0.83, 0.81, and 0.85, respectively.

CONCLUSION

The MLP network classifier based on contrast-enhanced CT can accurately predict CD20⁺ B expression in patients with PDAC.

Acute appendicitis complicated by mesenteric vein thrombosis: A case report

BACKGROUND

Acute appendicitis with mesenteric vein thrombosis (MVT) is an uncommon condition and usually lacks specific clinical manifestations, which leads to a high rate of misdiagnosis or delayed diagnosis, especially when it is accompanied by other abdominal diseases. Prompt and accurate recognition is vital for treatment and prognosis.

CASE SUMMARY

A 37-year-old woman had a history of acute metastatic right lower abdominal pain, nausea, and fever. A contrast-enhanced computed tomography (CT) scan showed a filling defect in the mesenteric vessels. The patient was diagnosed with acute appendicitis complicated by MVT and was treated with anticoagulation and intravenous antibiotics. The follow-up CT scan showed full resolution of the thrombosis and inflammation.

CONCLUSION

Clinical awareness is essential for recognizing MVT, especially when it is accompanied by other common acute abdominal diseases, such as acute appendicitis. Contrast-enhanced CT is helpful for the diagnosis of MVT and is recommended for patients with acute abdominal diseases.

Clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in liver

Objectives

To explore the clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in the liver and investigate the association between such small nodular lesions and the degree of tumor differentiation.

Methods

Combined imaging modalities were performed on 120 patients who were admitted by Linyi Maternal and Child Health hospital from December 2018 to December 2020 and diagnosed with hepatic nodular lesions. The CT scans were interpreted by two senior imageologists while the ultrasound scans were analyzed by two senior sonographers. A comparative analysis was carried out on different scan modes and the postoperative or post-puncture pathological results using the t-test, the χ2 test, and the Pearson's correlation analysis.

Results

Compared to the pathological results, definite diagnoses of 55 malignant cases were made using CECT alone, with the coincidence rate of 78.6%; CECT combined with CEUS formed correct diagnoses in 64 cases, and the coincidence rate was up to 91.4%. The difference between the two scan modes was statistically significant (p= 0.03). Based on pathological diagnosis, seventy out of the 120 cases of small nodular lesions were identified as malignant, while the other 50 cases were benign. The single imaging modality diagnosed 63 malignant and 57 benign nodules, whereas the combined modalities identified 68 malignancies and 52 benign conditions. Compared to CECT as a single imaging modality, the combined modalities showed a higher degree of sensitivity and accuracy, and the difference was statistically significant (sensitivity: p= 0.03; accuracy: p= 0.02); in the malignant cases, the magnitudes of contrast enhancement of CT and ultrasound imaging decreased with an increase in the degree of differentiation, indicating a negative correlation between these factors.

Conclusions

CECT combined with CEUS has a higher coincidence rate, greater sensitivity, and better diagnostic accuracy when being used for characterization and diagnosis of small nodular lesions in the liver. A higher degree of tumor differentiation means a decreased magnitude of contrast enhancement and a blurrier boundary, which indicates that CECT and CEUS are complementary to each other in classifying malignant liver nodules. The use of the combined imaging modalities shows clinical value for characterizing small liver nodules and predicting the degree of malignancy.

Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma

OBJECTIVE

To evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection.

METHODS

All 283 eligible patients were included retrospectively between January 2008 and December 2015, and assigned into the training cohort (n = 198) and the testing cohort (n = 85). We extracted radiomics features via handcrafted radiomics analysis manually and DL analysis of pretrained convolutional neural networks via transfer learning automatically. Support vector machine was adopted as the classifier. A clinical-radiological model for MVI status integrated significant clinical features and the radiological signature generated from the radiological model with the optimal area under the receiver operating characteristics curve (AUC) in the testing cohort. Otherwise, DL-based prognostic models were constructed in prediction of recurrence and mortality via Cox proportional hazard analysis.

RESULTS

The clinical-radiological model for MVI represented an AUC of 0.909, accuracy of 96.47%, sensitivity of 90.91%, specificity of 97.30%, positive predictive value of 83.33%, and negative predictive value of 98.63% in the testing cohort. The clinical-radiological models for identification of RFS and OS outperformed prediction performance of the clinical model or the DL signature alone. The DL-based integrated model for prognostication showed great predictive value with significant classification and discrimination abilities after validation.

CONCLUSIONS

The integrated DL-based radiomics models achieved accurate preoperative prediction of MVI status, and might facilitate predicting tumor recurrence and mortality in order to optimize clinical decisions for patients with early stage HCC.

Hemolymphangioma with multiple hemangiomas in liver of elderly woman with history of gynecological malignancy: A case report

BACKGROUND

Hepatic hemolymphangioma is an extremely rare benign congenital malformation composed of cystically dilated lymphatic and blood vessels, and they have nonspecific clinical symptoms and laboratory results. In this study, hepatic hemolymphangioma with multiple hemangiomas in an elderly woman was initially reported and analyzed.

CASE SUMMARY

A 61-year-old female patient, with a history of hysterectomy and bilateral adnexectomy, was referred to the hepatobiliary surgery department with the complaint of multiple hepatic hemangiomas that had been diagnosed 2 years prior in a preoperative contrast-enhanced computed tomography (CECT) examination. Upon entering our hospital, no abnormal physical examination and laboratory data were found. The latest CECT revealed a new 7.0 cm × 6.2 cm cystic-solid lesion with multiple internal divisions in segment II of the liver, with delayed CECT enhancement characteristics that presented as solid parts with internal division. On the positron emission tomography (PET)/CT, no significant uptake of ¹⁸F-fluorodeoxyglucse was observed. Finally, hepatic hemolymphangioma was confirmed based on the pathological and immunohistochemical results after surgery. At 1-year follow-up, her posthepatectomy evaluation was uneventful, and she had recovered full activity. In addition, no postoperative recurrent or residual lesion was found on CECT imaging.

CONCLUSION

Hepatic hemolymphangioma with multiple hemangiomas was reported and observed by CECT and PET/CT imaging.

The value of real-time contrast-enhanced ultrasound combined with CT enhancement in the differentiation of subtypes of renal cell carcinoma

AIM

This study aimed to evaluate the value of real-time contrast-enhanced ultrasound (CEUS) combined with contrast-enhanced computed tomography (CECT) in the differential diagnosis of clear cell renal cell carcinoma (CCRCC), papillary renal cell carcinoma (PRCC), and chromophobe renal cell carcinoma (CRCC).

MATERIALS AND METHODS

In the present study, 82 patients with CCRCC, 24 patients with PRCC, and 19 patients with CRCC were confirmed by pathology of the resected tumor. All patients were evaluated by CEUS and CECT before the operation. In addition, the contrast enhancement mode of CEUS and CECT and the contrast parameters of the region of interest (ROI) time-intensity curve between the lesions and the surrounding normal renal parenchyma by CEUS were compared and analyzed.

RESULTS

Compared with the pathological results, the diagnostic accuracy of ultrasound in the 3 groups was 87.8% (72/82), 83.3% (20/24) and 73.7% (14/19). There was no significant difference between CEUS and CECT in the diagnostic accuracy of all groups (P>0.05). Meanwhile, compared with the surrounding renal parenchyma by CEUS, 82.5% (66/80) of CCRCC lesions showed "fast-forward and fast/slow-retrograde," while 83.3% (20/24) of PRCC, and 84.2% (16/19) showed "slow-forward and fast/slow-retrograde." Significant differences in the enhancement modes of CEUS were found among the CCRCC, PRCC, and CRCC lesions (P < 0.05). And the enhancement modes could be quantitatively analyzed by the ROI time-intensity curve of the lesion. Moreover, lesions enhanced by CECT and 74.4% (61/82) of CCRCC lesions showed "fast-forward and fast/slow-retrograde," while 66.7% (16/24) of PRCC and 84.2% (16/19) of CRCC showed "slow-forward and fast/slow-retrograde." The contrast modes and enhancement uniformity of CEUS and CECT showed no significant differences among the CCRCC, PRCC, and CRCC lesions (P > 0.05).

CONCLUSION

CEUS and quantitative analysis of ROI time-intensity curve can be used for differential diagnosis of the 3 RCC subtypes. The combination of CEUS and CECT can help us differentiate RCC subtypes and is of great significance for clinical treatment strategies and prognostication.

Paraperitoneal herniation of the ureter

Ureteral herniation into the scrotum is rare and often associated with congenital abnormalities or postoperative anatomic changes. A high index of suspicion is needed to avoid intraoperative ureteric injuries. A 50-year-old man with ureteric herniation into an inguinoscrotal hernia reported acute left flank pain and had a history of recurrent urinary tract infections. Contrast-enhanced computed tomographic evaluation revealed a left ureter extending from the pelvis into the scrotum through the inguinal canal. Screening ultrasound of the scrotum revealed the intrascrotal extension of the ureter along with the other hernial contents and diagnosed as a Paraperitoneal inguinal herniation of the ureter. Various cross-sectional imaging modalities, including Ultrasound, provide good anatomic details that can diagnose the presence of a herniated ureter.

Impaired soft and hard callus formation during fracture healing in diet-induced obese mice as revealed by 3D contrast-enhanced computed tomography imaging

The impact of diabetes mellitus on bone fracture healing is clinically relevant as the patients experience delayed fracture healing. Even though efforts have been made to understand the detrimental effects of type 2 diabetes mellitus (T2DM) on the fracture healing process, the exact mechanisms causing the pathophysiological outcomes remain unclear. The aim of this study was to assess alterations in bone fracture healing (tibial fracture surgery, intramedullary pinning) of diet-induced obese (DIO) mice, and to investigate the in vitro properties of osteochondroprogenitors derived from the diabetic micro-environment. High-resolution contrast-enhanced microfocus X-ray computed tomography (CE-CT) enabled a simultaneous 3D assessment of the amount and spatial distribution of the regenerated soft and hard tissues during fracture healing and revealed that osteogenesis as well as chondrogenesis are altered in DIO mice. Compared to age-matched lean controls, DIO mice presented a decreased bone volume fraction and increased callus volume and adiposity at day 14 post-fracture. Of note, bone turnover was found altered in DIO mice relative to controls, evidenced by decreased blood serum osteocalcin and increased serum CTX levels. The in vitro data revealed that not only the osteogenic and adipogenic differentiation of periosteum-derived cells (PDCs) were altered by hyperglycemic (HG) conditions, but also the chondrogenic differentiation. Elevated PPARγ expression in HG conditions confirmed the observed increase in differentiated adipocytes in vitro. Finally, chondrogenesis-related genes COL2 and COL10 were downregulated for PDCs treated with HG medium, confirming that chondrogenic differentiation is compromised in vitro and suggesting that this may affect callus formation and maturation during the fracture healing process in vivo. Altogether, these results provide novel insights into the alterations of long bone fracture repair and suggest a link between HG-induced dysfunctionality of osteochondroprogenitor differentiation and fracture healing impairment under T2DM conditions.

Gastrointestinal neuroendocrine neoplasms (GI-NENs): hot topics in morphological, functional, and prognostic imaging

Neuroendocrine neoplasms (NENs) are heterogeneous tumours with a common phenotype descended from the diffuse endocrine system. NENs are found nearly anywhere in the body but the most frequent location is the gastrointestinal tract. Gastrointestinal neuroendocrine neoplasms (GI-NENs) are rather uncommon, representing around 2% of all gastrointestinal tumours and 20–30% of all primary neoplasms of the small bowel. GI-NENs have various clinical manifestations due to the different substances they can produce; some of these tumours appear to be associated with familial syndromes, such as multiple endocrine neoplasm and neurofibromatosis type 1. The current WHO classification (2019) divides NENs into three major categories: well-differentiated NENs, poorly differentiated NENs, and mixed neuroendocrine-non-neuroendocrine neoplasms. The diagnosis, localization, and staging of GI-NENs include morphology and functional imaging, above all contrast-enhanced computed tomography (CECT), and in the field of nuclear medicine imaging, a key role is played by ⁶⁸Ga-labelled-somatostatin analogues (⁶⁸Ga-DOTA-peptides) positron emission tomography/computed tomography (PET/TC). In this review of recent literature, we described the objectives of morphological/functional imaging and potential future possibilities of prognostic imaging in the assessment of GI-NENs.

Differences Between CT-Perfusion and Biphasic Contrast-enhanced CT for Detection and Characterization of Hepatocellular Carcinoma: Potential Explanations for Discrepant Cases

AIM

To compare the diagnostic value of liver perfusion computed tomography (PCT) and biphasic contrast-enhanced CT (bpCECT) for detection and characterization of hepatocellular carcinoma (HCC), and to identify potential causes for inter-modal discrepancies.

PATIENTS AND METHODS

In this retrospective study, 162 cases with a total of 325 HCC-typical lesions were evaluated using both PCT and bpCECT (mean time between examinations=15 days, range=0-13 days). HCC diagnosis was performed by multi-modality imaging including lesion growth at follow-up. For PCT, a total acquisition time of 40 s (26 measurements) each 1.5 s using 80 kV and 100 mAs, as well as 50 ml iodine contrast agent (at 5 ml/s) covering the entire liver was used. Mean arterial liver perfusion (ALP), portal venous perfusion (PVP) and hepatic arterial index (HPI) for both tumor and non-involved liver parenchyma; mean blood flow, blood volume and k-trans for tumor were quantified. Tumor localization, and size were registered. bpCECT consisted of unenhanced, arterial (30-33 s delay), and portal-venous (70-75 s) phases performed using 120 kV, 200-250 mAs, thin-slice reformates (<1 mm), 100 ml contrast agent (at 3 ml/s) followed by 50 ml saline flush. Finally, we divided the results according to detection by PCT only (i.e. missed by pbCECT), and by both PCT and pbCECT.

RESULTS

PCT detected 272 lesions compared to 217 with bpCECT only. HCCs in liver segments 4 and 5 were significantly better detected by PCT (p<0.005). Furthermore, PCT detected significantly smaller HCCs than did bpCECT (p<0.001). Lesions detected by both methods had significantly higher mean ALP (p=0.03) and HPI (p=0.02), and lower mean PVP (p=0.01). Tumor blood flow, blood volume and k-trans proved not to be significant for lesion detection. The mean ALP, HPI, and PVP in inconspicuous cirrhotic liver were also not significant for lesion detection. The PVP_(tumor)/HPI_(liver) ratio of detected lesions was significantly higher for PCT alone (p=0.04). Pretreated, still vital lesions were better detected by bpCECT.

CONCLUSION

Detection of smaller HCC lesions, lesions located in liver segments 4 and 5, as well as lesions presenting lower ALP and HPI, and higher PVP_(tumor)/HPI_(liver) ratio was better using both methods, emphasizing the important role of PCT.